Using system simulation to model the impact of human error in a maritime system

Abstract

Human error is cited as the predominant cause of transportation accidents. This paper describes the modeling of human error related accident event sequences in a risk assessment of maritime oil transportation in Prince William Sound, Alaska. The risk analysts were confronted with incomplete and misleading data that made it difficult to use theoretical frameworks. They were required, therefore, to make significant modeling assumptions in order to produce valid and useful results. A two stage human error framwork was developed for the Prince William Sound Risk Assessment based on interviews with maritime experts. Conditional probabilities implied by this framework were elicited from system experts (tanker masters, mates, engineers, and state pilots) and used within a dynamic simulation to produce the risk analysis base case results discussed. The ability to quantify the effectiveness of proposed risk reduction interventions aimed at reducing human and organizational error were limited by the level of detail described by the taxonomy of human error.